Heating System Research Articles

Sustainable hydrogen production by integrating solar PV electrolyser and solar evacuated tube collector with hybrid nanoparticles enhanced PCM

The investigation is motivated to analyze the influence of Phase change material (PCM), nano PCMs, and hybrid Nano PCM in sustainable hydrogen production systems. An emerging and highly effective method for hydrogen production involves the use of proton exchange membrane (PEM) technology, which separates water into its constituent parts through electrolysis. Its susceptibility to performance deterioration over time, however, demandsroutine maintenance and component replacement, which negatively impacts operational effectiveness and cost-effectiveness. In this study, the PEM system for electricity and water heating was integrated with the evacuated tube collector and photovoltaic panel to produce hydrogen. Additionally, hybrid Al2O3 and SiO2 nanoparticles with a combined concentration of 0.1 % in equal shares improved the thermal characteristics of PCM in heat exchangers. The research result shows that the heat exchanger of the ETSC circuit with the hybrid nanoparticles enhanced PCM demonstrated improved thermal performance as well as increased hydrogen production. With hybrid nanoparticles enhanced PCM in the heat exchanger, the maximum energy and electrical energy were observed as246.5 kWh and 44.7 kWh, respectively. The ETSC efficiency, electrical efficiency, and PEM electrolyser efficiency reached their highest points at 93.1 %, 15.5 %, and 39.2 %, respectively. Furthermore, hybrid nanoparticle-enhanced PCM produces an average of 25.9 g of hydrogen.

Maintaining a Sterile Environment: Validation and Qualification Strategies for Heating, Ventilation, and Air Conditioning Systems Adhering to Current Good Manufacturing Practices in Pharmaceutical Facilities.

This article presents a validation and qualification on heating, ventilation, and air conditioning(HVAC) systems. An HVAC system is required for suitable temperature maintenance, continuous air flow, and also keeping the air fresh, which ultimately helps in the prevention of cross-contamination and air accumulation and also ensures the availability of cool air on the premises. The quality of air ventilation in the pharmaceutical business has a considerable impact on worker safety, material efficacy, including raw materials, in-process items, and final products, and machinery. It ensures the optimal quality of air, as directed by the regulatory guidelines. Three degrees of validation are important for HVAC systems: installation qualification (IQ), performance qualification (PQ), and operational qualification (OQ). Air variations per hour, air circulation velocity, and air circulation pattern, pressure differential, recovery test for temperature and humidity, temperature and humidity uniformity, filter leak test, particle count, loss of utility test, compliance test, filter integrity test, and fresh air determination are some of the parameters to be assessed for the HVAC system validation.The validation tests that are mentioned in this article have acceptance criteria and procedures for conducting the tests that are provided by the current good manufacturing practices (cGMP) guidelines.

Environmental assessment of industrial aquaponics in arid zones using an integrated dynamic model

Land desertification, water scarcity, and food security challenges in arid zones are intensifying, driving the need for sustainable agricultural solutions like aquaponics. This study investigated innovative water and energy-saving strategies using an integrated dynamic model for an on-demand industrial aquaponics system in Israel. The model evaluated the performance of a recirculating aquaculture system (RAS), hydroponics system (HPS), and desalination unit (DU) by adjusting physical and operational parameters to optimize water and nutrient use efficiency, energy consumption, and yield. Optimizing the system design resulted in an aquaponics system with approximately 420 m3 RAS, 6.85 ha HPS and 40 m3/d DU, achieving phosphorus use efficiency of 96 %, a water use efficiency of 97 %, freshwater input of 1.5 L/day/m2, and energy consumption of 0.56 kWh/day/m2. To mitigate the challenges of extreme arid climates, evaporative cooling combined with outdoor shading and mechanical cooling was found to be a feasible option to control temperature and humidity in the greenhouse. Dehumidification technologies further improved system performance by recovering 22 % freshwater from seawater and increasing nitrogen use efficiency by 18 %. Achieving daily energy self-sufficiency required 4500 m2 photovoltaic panels and 5000 m2 solar heating system. While the system model was initially devised with a specific focus on conditions in Israel, it has been designed with scalability, allowing it to be adapted and applied extensively across diverse peri-urban regions and arid zones globally.

Forecasting of Daily Heat Production in a District Heating Plant Using a Neural Network

Artificial neural networks (ANNs) can be used for accurate heat load forecasting in district heating systems (DHSs). This paper presents an application of a shallow ANN with two hidden layers in the case of a local DHS. The developed model was used to write a simple application in Python 3.10 that can be used in the operation of a district heating plant to carry out a preliminary analysis of heat demand, taking into account the ambient temperature on a given day. The model was trained using the real data from the period 2019–2022. The training was sufficient for the number of 150 epochs. The prediction effectiveness indicator was proposed. In the considered case, the effectiveness of the trained network was 85% and was better in comparison to five different regression models. The developed tool was based on an open-source programming environment and proved its ability to predict heating load.

Thermodynamic analysis of heat pump heating system based on flue gas waste heat recovery

Abstract A lot of waste heat has not been recycled from exhaust gas of gas-fired condensing boilers. By enhancing boiler’s thermal efficiency, condensation latent and heat sensible heat should be deeply utilized. This article uses a heat pump to recover the waste heat from boiler flue gas to improve the heating efficiency of the unit. Taking an example of boiler unit, to illustrate the function of the thermodynamic capability, this article create a new heating system by installing a flue gas condenser and a low-temperature economizer, and a thermodynamic model. The experimental results show that if gas is cooling from 130°C to90°C and coefficient of performance(Cop ) is set by 1.746, by setting a low-temperature economizer, 20.87MW can be obtained from waste heat, which decrease water consumption of desulfurization tower 28.792t / h; due to that the heat pump use the condenser, waste heat can be recovered to 10.10MW and condensed water can be recovered to13.654t / h. When heat network’s return water increases, Cop decreases, but efficiency will increases in network; when outlet water in condenser increases, Cop and network efficiency decrease, but heat pump system increases in efficiency.

INDICATORS OF LOCAL ORAL IMMUNITY IN USERS OF NEW TYPES OF TOBACCO PRODUCTS

Introduction. The organs and structures of the oral cavity are among the first to come into contact with the aerosol when using electronic cigarettes and heated-tobacco products, and some of the aerosol components enter various biological fluids of the mouth, inevitably provoking a response of the body to external influences. One of the markers of the response are immunoglobulins, and their analysis is intended to help in studying the effect of electronic cigarettes and heated-tobacco products on humans. Objective. The aim of the study was to estimate changes in immunoglobulins A, G and M of gingival fluid, oral fluid and saliva among users of new types of tobacco products. Material and methods. The study included 4 groups of 5 people each: regular cigarette smokers, e-cigarette users, users of tobacco heating sys-tems and non-smokers. For laboratory studies, gingival fluid, saliva and oral fluid were taken from the subjects. Results. Various changes in the concentration of immunoglobulins relative to the control group were observed in all groups of smoking patients. Conclusion. The results may indicate inhibition of the function of local immunity both when exposed to tobacco smoke and when exposed to aerosol of heated-tobacco products or electronic cigarettes, which increases the vulnerability of organs and structures of the oral cavity to pathogenic microor-ganisms.

Simulation and analysis of solar-assisted air source heat pump heating system in severe cold region

Abstract severe cold and remote areas such as the west of Inner Mongolia, due to the vast land and sparse population, the coverage rate of heating pipes is low, resulting in high non-renewable energy consumption in building heating. To diminish the reliance on pollution energy and utilize sufficient solar energy resources, this study introduces a solar-assisted air source heat pump heating system (SASHP). Using TRNSYS to simulate the SAHSP’s system performance, the result indicates a good thermal environment between 12°C and 20°C. The average solar fraction in the coldest month of January is 33.45%, with a good heat collection efficiency. Compared with a single heating system, the SASHP’s total energy consumption was reduced by 45.11%, and SEER increased by 1.4 times. Optimization analysis displays that when the collector area is 100 square meters, and the tank volume is 5.5 cubic meters, the system achieves the best energy-saving effect. An optimized system can save 10,828.46 kg of standard coal annually during the heating period.

A step closer towards active and flexible consumers: enhancing involvement through energy consumption feedback

The level of consumer awareness and comprehension, during a period of abundant energy services, has a crucial role in their initial adoption and later engagement with the services. Digital energy platforms bring the ≫intangible electricity≪ closer to people’s daily lives and encourage new ways of thinking about and consuming energy. Energy feedback connects consumer’s consumption to their daily activities and provides insights. It enables them to learn about the consumption, learn how to reduce or optimise it and later, learn how to be flexible when needed. Besides investigating how familiar are the Slovenian households with their own consumption and energy related behaviour, the goal of this paper is also to investigate their preferences in visualizing their electricity consumption. The consumption estimation was validated on real case study using data from 642 Slovenian households. Results show that consumers that use electricity for space and water heating, underestimated their consumption up to 22.5%. A categorization of households based on their water and space heating systems is also presented.

Quasi-Two-Dimensional Code for the Calculation of Antenna Impedance of the ICR Heating System

Quasi-Two-Dimensional Code for the Calculation of Antenna Impedance of the ICR Heating System

Control of Thermal Uniformity in Microwave Heating Process by BPNN and Adaptive Particle Swarm Optimization

As China advances its green economy, innovative methods are being employed to enhance energy optimization and conservation within energy-intensive industries. Among these methods, microwave heating stands out due to its superior heating efficiency and lack of pollution. Nonetheless, uniform heating remains a challenge because the microwave absorption capacity of the heated medium varies with changes in heating time and temperature. To address this issue, an Adaptive Particle Swarm Optimization (APSO) neural network microwave system based on the Back Propagation Neural Network (BPNN) is proposed. This system leverages the fundamental principles of Particle Swarm Optimization (PSO), categorizing particle swarms into three types and iterating them through distinct processes to achieve optimal results. An APSO controller is designed based on system identification, adjusting the controller parameters according to the error between the real-time system output and the identification model. The feedback error is used as the fitness function in the PSO algorithm, continuously adjusting the weights and thresholds of the neural network. This intelligent control approach optimizes the microwave oven's input power to minimize the error between the actual temperature output and the identified temperature. The APSO controller is designed based on system identification, with the intelligently controlled microwave heating system adjusting its input power to minimize the error between the identified and actual temperature outputs. Unlike traditional Proportional Integral Differential (PID) and BPNN controllers, this approach calculates the output of the identified model and the error of the actual model, feeding this information back to the controller. The feedback error serves as the fitness function in the PSO algorithm, enabling continuous adjustment of the network's weights and thresholds to regulate the microwave equipment's output power, thereby ensuring the output temperature closely follows the preset temperature curve. Experimental results demonstrate that the actual output value of the system closely aligns with the original preset temperature curve, with a root mean square error of only 0.74. This designed identification and control system effectively achieves the desired outcome.

High-Power/High-Temperature Fluid Water Induction Heating System based on a SiC-MOSFET Single-Ended High-Frequency Resonant Inverter

High-Power/High-Temperature Fluid Water Induction Heating System based on a SiC-MOSFET Single-Ended High-Frequency Resonant Inverter

Impact of newer climate data for technical analysis of residential building energy use in the United States

In this study, we describe an analysis indicating the relative importance of newer hourly weather files for simulation analysis of the energy use of residential buildings in North America.Results show that older TMY3 (ending 2005) data compared with newer TMY2021 (2007–2021) data are less appropriate for the best prediction of low-energy buildings. The balance of heating and cooling is significantly altered in the more recent TMY files with potential impacts on best performing energy efficiency measures. With 64 high profile North American locations evaluated, we found heating to be approximately 11% lower with the newer data, while cooling was increased by a similar amount percentage wise. However, the dominance of space heating in North America made decreases to heating considerably larger in an absolute sense so that overall space conditioning energy fell.Small changes in annual temperature can have large impacts. For all electric homes with air source heat pumps, we found that a change of 1 °C to outdoor temperature can produce about a 19 % change in space conditioning energy. The newer data also shows increased average solar electric output from simulated rooftop photovoltaic systems, likely due to more sophisticated solar irradiance data. Water heating was about 3 % lower given rising groundwater temperatures and inlet water temperatures to water heating systems. Results also showed that the newer data tended to increase savings from comprehensive building efficiency efforts in all electric buildings. This largely takes place because higher temperatures in winter allow air source heat pumps to meet heating needs more efficiently. Generally, the direction of these influences ease pathways to reach zero energy buildings in North America.

Optimal scheduling of green heating systems in buildings considering economy and exergy efficiency

Green heating in buildings is of great significance to global energy conservation and emission reduction, and the design of optimal scheduling models is the key to achieve cost reduction and efficiency improvement in heating systems. For the building heating system containing multiple heterogeneous energy sources such as solar energy, air energy and electricity, a multi-objective optimal scheduling model is established with the goal of maximizing the exergy efficiency and minimizing the economic cost of the system, taking into account the quality difference of energy in the conversion process. Regarding the nonconvex and nonlinear constraints in the scheduling model, the incremental linearization method and Big-M method are used to linearize the transformation, and obtain the multi-objective mixed-integer linear programming model. Further, the ε-constraint method is used to solve the Pareto frontier of multi-objective optimization and the technique for order preference by similarity to ideal solution (TOPSIS) method is used to make decision. Finally, the simulation study of the model is carried out, and the results show that the proposed multi-objective optimal scheduling can balance the system operation economy and exergy efficiency compared with the belief rule base and evidential reasoning (BRB-ER) method, and the system’s daily economic cost are reduced by 9.66 %, 9.94 % and 17.24 %, respectively, and the system’s average daily coefficient of performance (COP) are improved by 4.66 %, 14.05 % and 13.22 %, respectively, on three typical days, it is verified that the proposed optimal scheduling model has better economy and exergy efficiency. The proposed multi-objective optimal scheduling model introduces exergy efficiency rather than energy efficiency as one of the optimization objectives of the heating system and reasonably solves the optimization model, which can provide a new idea and reference for the multi-objective optimal scheduling of the green heating system in buildings.

Optimal planning for integrated electricity and heat systems using CNN-BiLSTM-Attention network forecasts

This paper investigates optimal planning of integrated electricity and heat systems (IEHS) based on convolutional neural network-bidirectional long short term memory with attention mechanism (CNN-BiLSTM-Attention) network forecasts. Firstly, CNN and BiLSTM are employed to extract the spatio-temporal features of IEHS data, and the attention mechanism automatically assigns corresponding weights to BiLSTM to distinguish the importance of different time load sequences, then a combined CNN-BiLSTM-Attention network is constructed, which allows for a more accurate load forecasting. Furthermore, we establish optimal planning strategy to improve efficient operation and energy efficiency of the IEHS, in which the upper-level planning model with the optimization objective of minimizing comprehensive operation costs is formulated, the lower-level efficiency model aiming to balance revenue and cost is considered, then genetic algorithm and iterative solution strategy of Cplex solver are applied to optimize the bi-level objective functions. Simulation results show that the proposed CNN-BiLSTM-Attention model obtained smaller RMSE, MAE and MAPE compared to several other forecasting models. In addition, the optimization method could obtain global optimal solution of the bi-level objective functions, which improves the energy utilization efficiency of the IEHS.

Physicochemical properties of coconut inflorescence sap (neera) under double wall open heating system

Physicochemical properties of coconut inflorescence sap (neera) under double wall open heating system

Повышение энергетической эффективности работы тепловых сетей за счет утилизации тепловых потерь

The efficiency of thermal energy transfer, which is inevitably accompanied by heat losses through the insulation of pipelines, directly characterizes heating networks and centralized heat supply systems in general. The most important task in terms of current approaches to energy efficiency is to improve the efficiency of thermal energy transfer in modern heat supply systems. Currently known technical solutions to reduce heat losses through insulation of pipelines reduce heat losses, but not significantly. So, the purpose of this study is to develop a technical solution to reduce (even eliminate) standardized linear heat losses in heat supply networks of industrial enterprises. The authors have used methods of experimental research of heat transfer processes and mathematical modeling of heat and power equipment. A device for recycling heat losses is proposed. It is designed to reduce (even eliminate) normalized linear heat losses in heat supply networks of industrial enterprises. The permissible heat absorption of the device collector is determined, and a method for its regulation is described. An engineering method for calculation of the proposed device has been developed. The effectiveness of application of heat-reflecting screens in heating networks has been determined. A number of problems have been solved to improve the efficiency of heat supply systems of industrial enterprises using a device for recycling heat losses in the heating system channel.

SISTEMA DE UM AQUECEDOR SOLAR DE ÁGUA DE BAIXO CUSTO PARA BANHO FABRICADO COM TUBOS DE PVC

The growing demand for renewable and sustainable energy is driving the development of alternative solutions for water heating, such as low-cost solar heaters made from PVC pipes. This work presents a summary of the characteristics, advantages and disadvantages of this system, as well as important considerations for its implementation. The solar heating system with PVC pipes consists of solar collectors made from PVC pipes painted black, connected to a water tank through pipes. Cold water circulates through the tubes, absorbing solar energy and heating up. The heated water rises naturally to the water tank, where it is stored until use.

Deep spatio-temporal feature fusion learning for multi-step building cooling load forecasting

Accurate forecasting of building cooling load is essential for optimizing control strategies and energy efficiency in heating, ventilation, and air conditioning (HVAC) systems. However, existing machine learning and deep learning algorithms encounter challenges in addressing the dynamics and uncertain nature of cooling load demand, as they solely focus on temporal analysis. To tackle this issue, the paper proposes CRG-Informer, a deep learning approach that integrates spatio-temporal features to enhance multi-step predictive performance. Firstly, a time series spatial control relationship graph set is constructed based on the interconnected structure, static attributes, and control characteristics of the cooling system. Then, a graph neural network (GNN) is designed for graph embedding to extract spatial correlation information at each instance. Additionally, the Informer model with the ProbSparse self-attention mechanism is utilized to capture long-term temporal dependencies among input sequences. This integration of components enables feature fusion, and the proposed approach is evaluated using data from an office building in Hangzhou, China, over an entire cooling season. Extensive experiments were conducted to compare our method with five superior baseline models for 6, 12, 24, 72, and 144-step cooling load forecasting across four types of data acquisition intervals. The results demonstrate that the CRG-Informer, through spatio-temporal feature fusion, outperforms existing methods and provides a novel solution for improving cooling load forecasting performance.

The role of passive, active, and operational parameters in the relationship between urban heat island effect (UHI) and building energy consumption

The energy performance of buildings located in urban areas is strongly influenced by the UHI phenomenon, which usually leads to higher cooling energy consumption and lower heating energy consumption. Despite the known effects of UHI on building energy consumption, there is a lack of detailed knowledge on the role of building design and operational parameters in determining the effects of UHI on building energy use. To address this knowledge gap, this study analyzes the impacts of UHI on annual, heating, and cooling energy consumption of 16 prototype buildings located in 16 climate zones in the United States. The objective is to determine the relative relevance of building types (e.g., residential, commercial, healthcare facilities etc.), occupancy parameters (e.g., occupancy schedule) and the Heating, Ventilation and Air Conditioning (HVAC) systems in governing the impact of UHI on the building energy use matrices. Additionally, the thermal properties of the building envelope were evaluated to determine their relative importance in mitigating the effects of UHI on building energy performance. We found that, among the studies building types, while the cooling energy use of restaurant and outpatient healthcare buildings was most affected by UHI (higher cooling energy demands), the outpatient healthcare buildings were most impacted by UHI in terms of their heating energy use (lower heating energy use). The selection of HVAC systems type was found to have negligible influence on the energy impacts of UHI. Lastly, with regard to the thermal properties of the building envelope, window insulation was noted to be the most influential thermal property, followed by roof and wall insulation. Also, the role of insulation as well as other thermal properties was higher in the context of UHI’s impact on heating energy consumption as compared to cooling energy consumption. Not only are the results of this study useful for urban planning purposes to determine the vulnerability of different buildings to UHI, but they also are beneficial to UHI-resilient building designs.

Carbon nanodots-based interfacial nanofluid for high-performance solar-driven water evaporation

Solar steam generation through volumetric heating using nanofluids is a promising approach for wastewater treatment and desalination. However, low evaporation rate and slow response time to the change in solar intensity seriously affect their cumulative evaporation performance in practice. Here, we propose an interfacial nanofluid structure for high-performance solar-driven water evaporation using carbon nanodot (CDs) nanofluid and airlaid paper. CDs nanofluid transferred down through the paper from a source water tank to form an interfacial evaporation structure and ensure continuous water supply for evaporation. The solar conversion heat was only localized on a small amount of nanofluid on the paper resulting in low heat loss to the bulk nanofluid and a fast response time of within 2 min to reach a steady evaporation rate. In addition, the flowing nanofluid on the paper can absorb environmental energy to achieve high-rate evaporation of 1.93 kg m−2 h−1 under one sun irradiation. This study provides an effective strategy to improve the performance of volumetric heating systems for solar wastewater treatment and desalination.